Cost-controlled evaluations are reshaping how AI agents are benchmarked and developed, as highlighted by recent research from Princeton University (AI Agents That Matter). In an AI landscape often dominated by flashy, compute-intensive results, how can we ensure that these agents are truly efficient and practical for real-world use? This approach not only prevents misleading results […]